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Ameer BasitView profile

Senior Lecturer

• Workforce Engagement
• Organizational Behavior
• Human Resource Management
• +6 more

Dr. Ameer Basit is a Senior Lecturer in Management and Marketing at the University of Dundee’s School of Business, serving as Head of the Management and Marketing Team. He holds a PhD in Management from the National University of Malaysia (UKM) and brings over two decades of academic and industry experience. Prior to this role, he held leadership positions such as Dean, Head, and Programme Director at Pakistani universities. Education: PhD in Management, National University of Malaysia (2014) MBA (Details unspecified) Bachelor’s degree in Software Engineering (Implied by career background) Research Focus: Dr. Basit’s work centers on workforce engagement dynamics, integrating insights from computer science, social psychology, and organizational behavior. Key areas include talent acquisition, retention strategies, and the impact of workplace loneliness on well-being. His interdisciplinary approach leverages statistical modeling and data analytics to inform workforce management practices. Teaching: He teaches at all academic levels, including modules like Managing Teams in a Multicultural World , Strategic Management & Organisational Analysis , and Leadership and Decision Making . Professional Affiliations: Chartered Management Institute Membership (2024) Active in Scopus-indexed research with an h-index of 21 and 200+ citations Labs/Teams: Leads the Management and Marketing Team at Dundee, fostering collaborative research in organizational dynamics and workforce sciences.

Shahin ShahrampourView profile

Assistant Professor

• Machine Learning
• Optimization and Control
• Distributed Learning
• +5 more

Shahin Shahrampour is an Assistant Professor in the Department of Mechanical & Industrial Engineering at Northeastern University, with a courtesy appointment in Electrical & Computer Engineering. He holds a Ph.D. in Electrical & Systems Engineering from the University of Pennsylvania, an M.A. in Statistics from The Wharton School, and a B.S. in Electrical Engineering from Sharif University of Technology. Prior to Northeastern, he was at Texas A&M University and held a postdoctoral fellowship at Harvard University. Research Interests: Machine learning, optimization and control, distributed and sequential learning, with a focus on computationally efficient methods for data analytics. Specific areas include manifold optimization, online and reinforcement learning, non-convex optimization, and statistical signal processing. His work bridges theory and applications in networked systems and dynamic environments. Awards & Grants: Received a $500,000 NSF grant (2023) for distributed optimization in non-convex environments. Best Paper Award at IEEE ICASSP 2022 for contributions to signal processing. TEES Engineering Genesis Award (2020) for multidisciplinary research at Texas A&M. Principal Investigator on NSF-funded projects in collaborative online optimization and decentralized learning. Labs & Teams: Leads research in machine learning and control systems at Northeastern University, focusing on interdisciplinary challenges in distributed optimization and real-time learning. His lab emphasizes theoretical foundations and practical implementations in networked and dynamic systems.

• Productivity and Efficiency Analysis
• Environmental Economics and Policy
• Agricultural Economics
• +4 more

Dr. Atakelty Hailu is an Associate Professor at the UWA School of Agriculture and Environment, University of Western Australia. He serves as Graduate Research Coordinator and Coordinator of the Master of Agricultural Economics program. His educational background includes a BSc in Agricultural Economics from Alemaya University (1990) and PhD from University of Alberta (1998), with postdoctoral research at the Canadian Sustainable Forest Management Network. Research Expertise: Hailu's research spans productivity and efficiency analysis, environmental policy design, whole-farm bioeconomic modeling, agent-based computational economics, and non-market valuation. His current projects examine marine recreation valuation, economic-hydrologic modeling, China's carbon abatement costs, and human development indicators. Publication Focus: Hailu's recent publications reflect his interdisciplinary approach, addressing technical efficiency in agriculture across multiple countries (Vietnam, Pakistan, Kenya, Bangladesh), sustainable intensification practices, fisheries management innovations, and economic valuation methods. His work consistently integrates econometric methods with environmental policy applications. Awards and Recognition: Outstanding Doctoral Thesis Award (Canadian Agricultural Economics Society) Chancellor's Gold Medal for undergraduate achievements Publication of Enduring Quality Award (CAES, 2018) Graduate Supervision: Hailu has supervised numerous PhD students on projects including marine reserve effectiveness, agricultural efficiency in Vietnam and Ethiopia, conservation valuation in national parks, and fisheries management systems. Current PhD advisees focus on topics ranging from no-take marine reserves to efficiency in Kenyan agriculture. Research Funding: Hailu has secured multiple grants including projects on natural hazard economics (Bushfire CRC), marine conservation strategies (Australian Marine Conservation Society), environmental service policies (AgriFutures Australia), and conservation tender optimization (Dept of Agriculture).

Rebecca SeahView profile

Lecturer

• Mathematics Education
• Special Education
• Curriculum and Pedagogy
• +5 more

Rebecca Seah is a Lecturer in the School of Education at RMIT University. She holds an ORCID identifier (0000-0001-7307-2775) and is open to supervising Masters Research or PhD students. Her work focuses on Mathematics Education and Special Education, particularly in curriculum design, teacher professional learning, and supporting students with learning difficulties/disabilities. Rebecca has a doctorate investigating teacher professional knowledge and mathematics instruction for students with learning challenges. Prior to academia, she worked in special schools, early intervention programs for children with autism, and inclusive high school settings, where she developed integrated curricula for middle school students. She served as Acting Head of Special Education Services at Griffith University in 2009. Her research interests include Mathematical Reasoning, Learning Progressions, Design-Based Research, and STEM creativity frameworks. She contributed to the Reframing Mathematical Futures II project (2014–2018), developing geometric reasoning tasks for Years 7–10. This work earned her the RMIT Research Impact Award (2016) and the MERGA Beth Southwell Practical Implications Award (2018). Rebecca is a reviewer for journals like Mathematical Thinking and Learning and a regular presenter at conferences. She collaborates with organizations such as the Mathematics Education Research Group of Australasia and the Mathematics Associations of Victoria. Her industry experience includes roles in early childhood education and training workshops for people with special needs.

Fred PopowichView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Big Data
• +4 more

Fred Popowich is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He holds adjunct positions at Dalhousie University's Faculty of Graduate Studies and is an Associate Member of SFU's Department of Linguistics and Cognitive Science Program. His academic career began post-PhD (Cognitive Science/Artificial Intelligence, University of Edinburgh, 1989) and has spanned over three decades at SFU. Education: PhD in Cognitive Science/Artificial Intelligence (University of Edinburgh, 1989); M.Sc. and B.Sc. in Computing Science (Simon Fraser University and University of Alberta, 1985/1982). Research focuses on natural language processing (NLP), machine translation, intelligent systems, and big data applications. He directs SFU’s Big Data Initiative and leads the Natural Language Laboratory, supervising MSc/PhD students in computing science. His work includes developing systems for smart homes, toxic language detection in social media, and energy grid analysis. Industry roles include co-founding Axonwave Software (as CTO/President) and contributing to technology commercialization. Current projects address EV charging impacts, personalized learning systems, and real-time load monitoring. Publications span machine translation, sentiment analysis, and NLP applications in education and energy systems. His work bridges theoretical computer science with practical applications in healthcare, smart cities, and education.

• Marketing
• Business Analytics
• Organizational Behavior
• +3 more

Steven D. Silver is a Professor in the Department of Marketing and Business Analytics at the Lucas College and Graduate School of Business, San José State University. He holds a Ph.D. from the University of California, Berkeley (1983). His research focuses on knowledge use in leisure and work contexts, organizational information exchange, and the impact of social status on idea generation processes in both face-to-face and computer-mediated environments. Silver has taught courses such as Business Statistics and Marketing Research, emphasizing data-driven decision-making and market analysis. His work bridges marketing theory with practical applications in business analytics and organizational behavior. Research interests include leveraging interdisciplinary approaches to study how knowledge is consumed and disseminated in professional and leisure settings. Notable contributions include exploring how status dynamics influence collaborative innovation processes. His publications span academic articles and a seminal book on knowledge consumption patterns. Teaching responsibilities have included both online and traditional formats, reflecting his adaptability to evolving educational platforms. While no specific grants or awards are detailed, his academic contributions align with institutional priorities in business education and applied research. Contact him via steven.silver@sjsu.edu or at office BT 758 for further inquiries.

Sven ScheweView profile

Professor

• Automata Theory
• Game Theory
• Formal Verification
• +12 more

Sven Schewe is a Professor in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. He leads the AI Section and is a founding member and former leader of the Verification Group. He also has secondary affiliations with the Algorithms, Complexity Theory and Optimisation Group and the Institute for Risk and Uncertainty. Research Interests: His research centers on automata theory and game theory, particularly their applications in the verification and synthesis of reactive and safety-critical systems. He investigates infinite-duration games, automata over infinite words and trees, and develops algorithms and tools for automated verification, synthesis, and learning of optimal control strategies. His work extends to reinforcement learning with formal guarantees, cyber-physical systems, and AI safety. Recent Research Trends: His recent publications demonstrate a strong integration of formal methods with machine learning, particularly in adversarial training, neural network robustness, and model-free reinforcement learning under omega-regular objectives. He also applies formal reasoning to interdisciplinary domains such as chemical space exploration and materials science. Scientific Awards: Finalist for the ERCIM Cor Baayen Award 2010 Dr. Eduard Martin Preis 2009 GI Dissertation Award 2008 Advising and Grants: He actively supervises numerous PhD students and postdoctoral researchers. He is Principal Investigator (PI) or Co-Investigator (CI) on multiple major grants, including EPSRC Programme Grants, Royal Society Fellowships, and Horizon Europe projects. His funded research spans topics such as game theory, verification, synthesis, reinforcement learning, and risk analysis. He has hosted visiting researchers and collaborated internationally with institutions in Germany, France, India, Taiwan, and the US. Labs and Teams: He co-founded and led the Verification Group and previously led the AI Section at the University of Liverpool. These groups focus on formal methods, automata, games, and their applications in AI and safety-critical systems.

Corey PeltierView profile

Associate Professor

• Special Education
• Mathematics Education
• Single-Case Research Designs
• +3 more

Corey Peltier is an Associate Professor of Special Education in the Department of Educational Psychology at the University of Oklahoma, affiliated with the Jeannine Rainbolt College of Education . His work focuses on enhancing mathematical outcomes for students with disabilities through rigorous research methodologies like single-case experimental designs (SCEDs) and meta-analyses. He collaborates on initiatives such as The Science of Math and co-founded the open-access journal Single-Case in the Social Sciences to advance evidence-based practices. Research Interests: Effective interventions for students with disabilities in mathematics Methodological rigor in single-case research designs Systematic reviews and meta-analyses to inform educational practice Recent work emphasizes: Disseminating research through accessible platforms Addressing implementation barriers in special education Advocating for inclusive pedagogy and policy alignment Key contributions include frameworks for mathematics interventions, critiques of graphing practices in SCED studies, and collaborations to improve teacher preparation. His research bridges gaps between academic theory and classroom practice, particularly in high-need areas like rural education and behavioral disorder support.

• Sports Criminology
• Violence in Sports
• Social Perspectives of Sports
• +4 more

Dr Victoria Silverwood is a Researcher in Criminology at the School of Social Sciences, Swansea University . Her work uniquely bridges criminology with sports studies, focusing on the cultural and social dimensions of sports-related head injuries and legitimised violence in contact sports. She is affiliated with the Swansea Centre of Research into Sports and Society (SCORSS) , a multidisciplinary group examining sports and leisure cultures. Research Interests include: Sports-related concussion as a social issue Critical Sports Criminology Violence and harm in professional ice hockey (NHL, UK Elite Ice Hockey League) Legitimisation of violence in sports subcultures Policy implications for child protection and fostering wellbeing Her publications over 16 years reveal a consistent focus on sports violence , public health , and social justice . She utilizes mixed-method research designs and ethnographic approaches to dissect spectator and athlete behaviors. Silverwood actively engages the public, as evidenced by her Hay Festival 2023 talk and collaborations with projects like StreetSnap and Flip the Streets . Contact: v.s.m.silverwood@swansea.ac.uk

Alexander Miserlis HoyleView profile

Researcher

• Computational Social Science
• Natural Language Processing
• Machine Learning
• +6 more

Alexander Hoyle is a Researcher at the ETH Zürich AI Center, concurrently contributing to natural language processing/machine learning and social science groups. He holds a PhD in Computer Science from the University of Maryland (advised by Philip Resnik) and a Master's in Computational Statistics from University College London (advised by Sebastian Riedel and Jeff Mitchell). His research focuses on computational social science, emphasizing methods for latent construct identification (e.g., topic models, ideal point models) and evaluation frameworks grounded in validity. Key areas include bias/fairness in AI, political science applications, and mental health constructs like suicidality. He pioneered frameworks like PairScale (attitude measurement via pairwise comparisons) and TopicGPT (prompt-based topic modeling). Education: PhD in Computer Science, University of Maryland (2020-2023) MS in Computational Statistics & Machine Learning, University College London (2018) Bachelor's degree (pre-PhD details omitted) Research Interests: Combining NLP with social science needs, particularly in evaluation rigor and interpretability. Active in interdisciplinary work between NLP and computational social science (e.g., measuring attitude evolution on Reddit, improving topic model validity). Advocates for human-in-the-loop approaches to address LLM limitations in tasks like document clustering and sentiment analysis. Grants & Projects: Contributed to a landmark $2.2B DOJ settlement on NYC public housing via econometric modeling at The Brattle Group. Active in graduate labor advocacy (Maryland state legislature testimony) and mentorship (Científico Latino's mentorship program). Labs & Teams: Leads initiatives at the ETH Zürich AI Center, collaborating with groups like Microsoft Research (FATE) and AI2's AllenNLP. Involved in multi-university projects (e.g., University of Maryland's Computational Linguistics lab).

Helen RobertsView profile

Professor

• Luminescence Dating
• Quaternary Science
• Geomorphology
• +7 more

Helen Roberts is a Professor in the Department of Geography and Earth Sciences at Aberystwyth University , where she has been a key figure since joining as a post-doctoral researcher in 1998 and becoming a Lecturer in 2005. She currently serves as Co-Director of the Aberystwyth Luminescence Research Laboratory (ALRL) and holds leadership roles in international bodies such as INQUA’s Stratigraphy and Geochronology Commission. PhD, University of Liverpool Her research focuses on luminescence dating of Quaternary sediments , with applications in understanding geomorphic change, coastal dynamics, paleoclimate, and human evolution . She has led major projects such as EQUATE and CREDit , funded by Horizon Europe and NERC, and has been involved in international drilling initiatives in Ethiopia and Italy. Her work integrates fieldwork, laboratory innovation, and data modeling to reconstruct environmental change over hundreds of thousands of years. Analysis of her recent publications reveals a strong emphasis on refining luminescence techniques (e.g., pIRIR, TL in calcite), applying them to critical paleoenvironmental archives (lake sediments, loess, glacial deposits), and linking climate variability to human evolution. Her interdisciplinary approach spans geochronology, sedimentology, and paleoanthropology. Fellow of the Learned Society of Wales (2023) Professor Roberts has supervised PhD students, including Svenja Riedesel, and secured significant research grants from NERC, UK Space Agency, and the Welsh Government. She actively contributes to scientific discourse through media engagement and public outreach. Her work supports UN Sustainable Development Goals related to climate action and life on land. She leads and participates in numerous international collaborations and professional committees, reflecting her standing in the Quaternary science community. She is involved in several research groups and laboratories, most notably the Aberystwyth Luminescence Research Laboratory , where she co-directs methodological development and application of luminescence dating techniques. Her team collaborates globally on projects involving terrestrial archives, paleoclimate modeling, and human evolution.

• Machine Learning
• Atmospheric Science
• Remote Sensing
• +3 more

Tao Shi serves as an Assistant Professor in the Department of Statistics at Ohio State University. Dr. Shi completed doctoral studies at the University of California, Berkeley, receiving a Ph.D. in Statistics in 2005. Dr. Shi's academic foundation was established through doctoral research conducted under Professor Bin Yu at UC Berkeley. The dissertation, titled Polar Cloud Detection using Satellite Data with Analysis and Application of Kernel Learning Algorithms , represents a significant interdisciplinary contribution at the intersection of statistical methodology and environmental science. Primary Research Focus: Application of machine learning techniques to environmental satellite data Specialization: Polar region cloud identification systems Technical Expertise: Kernel-based algorithms for complex atmospheric pattern recognition Domain Knowledge: Integration of statistical learning with climate observation systems With two decades of post-PhD experience, Dr. Shi's research program demonstrates how advanced statistical methods can address critical challenges in climate monitoring and atmospheric science. The work bridges theoretical machine learning with practical environmental applications, particularly in analyzing satellite imagery of polar regions.

• Aboriginal and Torres Strait Islander Health and Wellbeing
• Epidemiology
• Knowledge Translation
• +3 more

Makayla-May Brinckley is an Indigenous Research Fellow at the Australian National University (ANU) within the ANU College of Law, Governance and Policy and the National Centre for Aboriginal and Torres Strait Islander Wellbeing Research . A Wiradjuri woman from Cootamundra, NSW, she contributes to projects like Mayi Kuwayu , the National Study of Aboriginal and Torres Strait Islander Wellbeing. Education : Bachelor of Arts/Bachelor of Science (Psychology Honours) from ANU (2019) Research Interests encompass holistic health, strengths-based approaches, and decolonial frameworks for Aboriginal and Torres Strait Islander populations. Her work spans epidemiology, knowledge translation, and cultural indicators, often employing longitudinal and community-driven methodologies. Articles highlight trends in Indigenous adolescent health , social determinants of smoking behavior , cultural wellbeing metrics , and psychological distress linked to discrimination . Publications appear in journals like The Lancet , Health Promotion International , and BMC Public Health . Projects include developing baseline data on cultural determinants of health, mental health assessments during the Voice to Parliament Referendum, and advising on Indigenous data governance structures.

Noortje VenhuizenView profile

Assistant Professor

• Computational Semantics
• Discourse Processing
• Language Comprehension
• +3 more

Noortje Venhuizen is an Assistant Professor in the Department of Cognitive Science and Artificial Intelligence at the Tilburg School of Humanities and Digital Sciences, Tilburg University. She serves as Academic Director for the BSc Cognitive Science and Artificial Intelligence program since 2024, and has held academic positions at Saarland University (2015-2022) including roles as Scientific Staff member and Principal Investigator in SFB 1102 projects. PhD in Computational Semantics (University of Groningen, 2015) MSc in Logic (ILLC, University of Amsterdam, 2011) BSc in Artificial Intelligence (Utrecht University, 2009) Her research focuses on expectation-based language comprehension, neurocomputational modeling of semantic processing, distributional formal semantics, and pragmatic reasoning in discourse. Key contributions include PDRT-SANDBOX (Haskell NLP library) and DFS Tools (Prolog implementation of distributional formal semantics). Recent publications (2023-2025) explore multimodal word meaning, informativity in reference production, and neurocognitive models of surprisal processing. Her work combines formal semantics with cognitive neuroscience and computational modeling. LOT Grotevragenprijs essay contest - Second Prize She has presented research at major conferences including CogSci, AMLaP, and Sinn und Bedeutung. Current teaching includes courses on artificial intelligence, statistics, and semantic theory.

• Mathematics of Voting and Choice
• Algebraic Geometry
• Representation Theory
• +15 more

Karl-Dieter Crisman is Professor of Mathematics and Computer Science at Gordon College, where he also serves as Campus Organist. He is affiliated with the School of Science and Health and the Herschend School of Education. His academic work bridges pure mathematics, pedagogy, and interdisciplinary scholarship. Education: PhD in Mathematics, University of Chicago; M.Mus., Roosevelt University; Undergraduate, Northwestern University. Research: Focuses on the mathematics of voting and choice, algebraic geometry (especially zero-cycles and hyperplane arrangements), representation theory in social choice, and the history of mathematics (notably Marin Mersenne). Open Source & Education: Lead developer and author of the open textbook Number Theory: In Context and Interactive , widely used and praised. Active contributor to SageMath and PreTeXt projects. His research in voting theory explores generalized voting procedures on posets and cyclic orders, often using representation-theoretic techniques. His pedagogical scholarship promotes inquiry-based learning, service-learning, and technology integration, particularly through Sage cells. He has written extensively on the connections between mathematics, music, and theology. He has been recognized with the 2024 MAA Northeastern Section Award for Distinguished Teaching. He serves as Vice Chair (and future Chair) of the MAA Northeastern Section and was Associate Editor for PRIMUS. Professional Service: Organizes the Gordon Math Forum, Faculty Forum colloquium, and the North Shore Undergraduate Mathematics Conference; previously chaired the Pike Honors Program. Advising: Mentors undergraduate research in voting theory, algebra, topology, and the history of mathematics. Grants: Received support from the American Institute of Mathematics' SQuaREs program for collaborative research. He frequently gives talks on voting theory, SageMath, open textbooks, and the life of Marin Mersenne.